In a measuring system comprising a plurality of sensors, it is often desirable to collect sensor values from all sensors at the same time in order to produce a connected data record. By way of example, if the position of a point object is to be determined completely at a specific time, the three corresponding coordinates have to be collected at the same time.
One option to this end is to emit a trigger signal simultaneously to all sensors involved, which trigger signal triggers measured value collection by the individual sensors. A problem herein is that, in general, it is nevertheless not the case that all measured values are collected at a single time due to time delays of different types. By way of example, delays emerge due to different signal run-times of trigger signal and measurement signals or due to varying sensor startup times and sensor latency times, the duration of which moreover may vary depending on process or surroundings. According to the prior art, the problem can be solved in some cases by virtue of emitting such a synchronization signal not simultaneously to all sensors, but with a time offset, adapted to the respective delay times. However, this means additional outlay and presumes knowledge of the delay times, which may not be able to be established in all cases.
There are further problems in the case of continuous measurements, i.e. during continuous production of value tuples respectively having one value from various sensors. The individual sensors are usually clocked differently, due to, inter alia, different sensor dead times, so that even if first measurements are triggered simultaneously, the following measurements will no longer be simultaneous, or it is necessary to wait until the individual clocks once again enable a common measurement time, leading to idle times of individual sensors. An approximate solution consists of making do with only approximate synchronicity of the individual sensor values and considering those sensor values whose time interval is lowest or which do not exceed a temporal maximum interval as being a connected data record.
Another approximate solution emerges by virtue of extrapolating or interpolating approximate sensor values, from collected sensor measured values, in respect of a desired common time.
Here, the term “sensor measured value” or “measured value” is understood to mean a collected sensor value, i.e. a value which is directly available by a measurement of the sensor. The collection time of a measured value is the time at which the measured value was actually measured. The latency time is that time interval passing from this time until the time at which this measured value is available.
An extrapolated or interpolated sensor value is in contrast to a measured value. This refers to a value calculated from measured values. The calculation is brought about on the basis of an extrapolation rule for a value of the time variables to be predetermined. The term “extrapolation time” means such a predetermined time value.
The term “sensor value” is understood to mean an overarching term, which is used if there is no need for a restriction to one of the two options. Accordingly, the term “recording time” comprises both a collection time and an extrapolation time.
Using extrapolation or interpolation for predetermined time values, it is possible to provide sensor values with constant time intervals by appropriate clocks, but not sensor values with equidistant spacing.
By way of example, such equidistant sensor values are desired when detecting surfaces. To this end, use is often made of methods which scan the topography of a structure, such as e.g. a building, in sequence and make recordings in the process, as a result of which a 3D point cloud is produced. A conventional approach lies in scanning by means of a laser scanner. The latter consists of a laser rangefinder and a device, usually developed as two angle sensors, for continuously aligning the laser rangefinder or the laser beam, brought about by rotation about two axes, and detecting the two direction angles. Accordingly, the position of a surface point is generally determined in spherical coordinate form by virtue of, firstly, the two alignment angles being measured relative to the two rotational axes and, secondly, the distance to the sighted surface point being measured by means of the laser beam.
Here, the time delays already mentioned above cause difficulties, in particular those caused by the latency time of the angle sensor which, in the case of an angle sensor in the prior art, may be e.g. 600 ns. A distance measurement at a specific angle can only be triggered at a time offset by at least this time interval; however, by then, the alignment has already changed, i.e. no longer corresponds to the determined angle. As a result of this, distance and angle do not relate to precisely the same surface point. A possible downstream interpolation of a distance value to the matching alignment time is connected with disadvantages since there may be discontinuities which cannot be estimated between two distance values, caused by irregular surface profiles.
In order to produce a regular point scanning pattern, it is accordingly important in scanners of the prior art for the distances already to be registered during the recording at equidistant angle intervals for both direction angles. Generally, the rotational speeds about the two rotational axes are not the same, but the angular velocity in one direction is significantly greater than in the other one such that line-by-line scanning is possible.
Since, according to the prior art, equidistant measuring of the angle sensor values is attempted to be achieved via a constant measuring frequency in the case of an unchanging angular velocity, the challenges for the uniformity of the rotation about the fast rotational axis are correspondingly great. Ensuring such precise clocking places high demands on the systematic accuracy of the corresponding angle sensor.
One option for solving problems in relation to the accuracy of measurements lies in extrapolation. WO 2010/139964 A2 discloses a method for operating a position encoder, by means of which random inaccuracies in an individual measurement can be identified. A position value is extrapolated from at least one position measured value in such a way that it is associated with the same time as a currently measured position value. A random error in the current measurement, for example an incorrectly read-out position code, causes a conspicuously large discrepancy between the two, as a result of which the measurement inaccuracy can be identified. The position measured value can then be replaced by the corresponding calculated value thereof, as a result of which the reliability of individual position values is increased.
A disadvantage of the method described in WO 2010/139964 A2 lies in the fact that an extrapolated position value is related directly to one measured value. This does not reduce the requirements on the systematic accuracy of the position sensor in respect of the provision of sensor values with equidistance from one another. An irregularity in this respect in the collected measured values will be transferred to the calculated values. Moreover, a disadvantage is that, as a result of this direct reference, the provision of sensor values is not decoupled from the sensor dead time and accordingly there is no provision of additional position values.